Analysis of drought patterns and categories based on the Standard Precipitation-Temperature Index (SPTI): application of fuzzy c-means clustering and principal component analysis

ArticleAçık Erişim

Özet

This study deals with climate variability issues in the Kebir Rhumel basin, situated in northeastern Algeria. This region is experiencing significant changes in climate parameters, which will affect the region’s water resources, agriculture, and overall ecosystem health. The main goal of this study is to examine the severity and frequency of drought from 1981 to 2019. It used the Standard Precipitation-Temperature Index (SPTI), which was recently developed, and clustering methodologies such as c-means and k-means to examine the variation in rainfall patterns characterized by intervals of intense drought and heavy precipitation. These methods help assess the impact of these disturbances in water availability, which result in challenges for agricultural productivity and water management. Additionally, this study points out the significant trend in temperatures over the reported timeline, which aligns with global warming patterns; this intensifies the effect of drought and impacts the region’s water resources. The southeastern and western parts of the basin are areas that experience continuous extreme drought, and different levels of severe drought have been observed over decades. When comparing the results with existing methods, this research has revealed unique climatic trends in this basin area through clustering techniques applied to SPTI results. In particular, 45% of the stations indicate moderate wetness, 35% of the stations experience extreme wetness, and 20% of the stations are extremely dry. Each of these climatic patterns poses distinct challenges for water resource management. These findings demonstrate the complex interplay between rainfall variability, temperature increases, and drought severity. They underscore the urgent need for adaptive water management strategies and plans to address climate change impacts. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/ebyu/10601Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1007/s11069-025-07271-7Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorBerhail, Sabri
dc.contributor.authorKatipoğlu, Okan Mert
dc.date.accessioned2026-10-18T20:25:47.360023002Z
dc.date.available2026-10-18T20:25:47.360023002Z
dc.date.issued2025
dc.description.abstractThis study deals with climate variability issues in the Kebir Rhumel basin, situated in northeastern Algeria. This region is experiencing significant changes in climate parameters, which will affect the region’s water resources, agriculture, and overall ecosystem health. The main goal of this study is to examine the severity and frequency of drought from 1981 to 2019. It used the Standard Precipitation-Temperature Index (SPTI), which was recently developed, and clustering methodologies such as c-means and k-means to examine the variation in rainfall patterns characterized by intervals of intense drought and heavy precipitation. These methods help assess the impact of these disturbances in water availability, which result in challenges for agricultural productivity and water management. Additionally, this study points out the significant trend in temperatures over the reported timeline, which aligns with global warming patterns; this intensifies the effect of drought and impacts the region’s water resources. The southeastern and western parts of the basin are areas that experience continuous extreme drought, and different levels of severe drought have been observed over decades. When comparing the results with existing methods, this research has revealed unique climatic trends in this basin area through clustering techniques applied to SPTI results. In particular, 45% of the stations indicate moderate wetness, 35% of the stations experience extreme wetness, and 20% of the stations are extremely dry. Each of these climatic patterns poses distinct challenges for water resource management. These findings demonstrate the complex interplay between rainfall variability, temperature increases, and drought severity. They underscore the urgent need for adaptive water management strategies and plans to address climate change impacts. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.
dc.description.sponsorshipThe authors thank the National Agency of Hydraulic Resources (ANRH) for providing the observed monthly precipitation and temperature data, as well as the Editor and the anonymous reviewers for their contributions to the content and development of this paper.
dc.identifier.doi10.1007/s11069-025-07271-7
dc.identifier.eissn1573-0840
dc.identifier.endpage12051
dc.identifier.issn0921-030X
dc.identifier.issue10
dc.identifier.scopus2-s2.0-105003499458
dc.identifier.startpage12025
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/10601
dc.identifier.volume121
dc.identifier.wosWOS:001475911200001
dc.language.isoen
dc.publisherSpringer Science and Business Media B.V.
dc.relation.ispartofNatural Hazards
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectC-means
dc.subjectCluster analysis
dc.subjectDrought
dc.subjectK-means
dc.subjectPrecipitation
dc.subjectTemperature
dc.subjectWater resources
dc.subjectAlgeria
dc.subjectclimate effect
dc.subjectclimate variation
dc.subjectglobal warming
dc.subjectprecipitation (climatology)
dc.subjectprincipal component analysis
dc.subjectrainfall
dc.subjecttemperature effect
dc.subjectwater availability
dc.subjectwater management
dc.subjectwater resource
dc.titleAnalysis of drought patterns and categories based on the Standard Precipitation-Temperature Index (SPTI): application of fuzzy c-means clustering and principal component analysis
dc.typeArticle
dspace.entity.typePublication
rdl.citation.scopus5
rdl.citation.wos5
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)